Method and apparatus for control of a hybrid electric vehicle to achieve a target life objective for an energy storage device

ABSTRACT

A method for determining a preferred operating gradient for use in attaining a life objective for an electrical energy storage device in a hybrid vehicle is disclosed. A present state-of-life of the electrical energy storage device is provided and a life target for the electrical energy storage device is established as a predetermined limit in a predetermined metric at a predetermined state-of-life of the electrical energy storage device. A state-of-life gradient is then determined with respect to the predetermined metric which converges the state-of-life of the electrical energy storage device to the life target.

TECHNICAL FIELD

This invention pertains generally to management of an electrical energystorage device. More particularly, the invention is concerned withachieving a target life for an electrical energy storage device.

BACKGROUND OF THE INVENTION

Various hybrid propulsion systems for vehicles use electrical energystorage devices to supply electrical energy to electrical machines,which are operable to provide motive torque to the vehicle, often inconjunction with an internal combustion engine. One such hybridpowertrain architecture comprises a two-mode, compound-split,electromechanical transmission which utilizes an input member forreceiving power from a prime mover power source and an output member fordelivering power from the transmission to a vehicle driveline. First andsecond electric machines, i.e. motor/generators, are operativelyconnected to an energy storage device for interchanging electrical powertherebetween. A control unit is provided for regulating the electricalpower interchange between the energy storage device and the electricmachines. The control unit also regulates electrical power interchangebetween the first and second electric machines.

One of the design considerations in vehicle powertrain systems is anability to provide consistent vehicle performance and component/systemservice life. Hybrid vehicles, and more specifically the battery packsystems utilized therewith, provide vehicle system designers with newchallenges and tradeoffs. It has been observed that service life of anelectrical energy storage device, e.g. a battery pack system, increasesas resting temperature of the battery pack decreases. However, coldoperating temperature introduces limits in battery charge/dischargeperformance until temperature of the pack is increased. A warm batterypack is more able to supply required power to the vehicle propulsionsystem, but continued warm temperature operation may result indiminished service life.

Modern hybrid vehicle systems manage various aspects of operation of thehybrid system to effect improved service life of the battery. Forexample, depth of battery discharge is managed, amp-hour (A-h)throughput is limited, and convection fans are used to cool the batterypack. Ambient environmental conditions in which the vehicle is operatedhas largely been ignored. However, the ambient environmental conditionsmay have significant effect upon battery service life. Specifically,same models of hybrid vehicles released into various geographic areasthroughout North America would likely not result in the same batterypack life, even if all the vehicles were driven on the same cycle. Thevehicle's environment must be considered if a useful estimation ofbattery life is to be derived. Additionally, customer expectations,competition and government regulations impose standards of performance,including for service life of battery packs, which must be met.

End of service life of a battery pack may be indicated by ohmicresistance of the battery pack. The ohmic resistance of the battery packis typically flat during much of the service life of the vehicle andbattery pack however, thus preventing a reliable estimate of real-timestate-of-life (‘SOL’) of the battery pack throughout most of the servicelife. Instead, ohmic resistance is most useful to indicate incipient endof service life of the battery pack.

It is desirable to have a method and apparatus to provide a control ofoperation of an electrical energy storage system, including forapplication on a gasoline/electric hybrid vehicle that controlsoperation based upon a targeted service life of the electrical energystorage device.

SUMMARY OF THE INVENTION

A hybrid vehicular powertrain includes first and second electricmachines, each machine operable to impart torque to a two-mode,compound-split electromechanical transmission having four fixed gearratios and two continuously variable operating modes. A method foroperating the hybrid electric powertrain includes providing presentstate-of-life of the electrical energy storage device and establishing alife target for the electrical energy storage device as a predeterminedlimit in a predetermined metric at a predetermined state-of-life of theelectrical energy storage device. A state-of-life gradient is thendetermined with respect to the predetermined metric which converges thestate-of-life of the electrical energy storage device to the lifetarget. The electric machines are operated such that electrical energystorage device state-of-life substantially tracks the state-of-lifegradient based on the determined changes in state-of-life.

Preferably, the predetermined state-of-life of the electrical energystorage device is indicative of the end of life of the electrical energystorage device. In accordance with one alternative, the metric includeselapsed service time of the electrical energy storage device. Inaccordance with another alternative, the metric comprises vehicledistance traveled. In accordance with another alternative, the lifetarget is based upon a predetermined limit in one of elapsed servicetime of the electrical energy storage device and vehicle distancetraveled. The life target is preferably normalized with respect to theone of elapsed service time of the electrical energy storage device andvehicle distance traveled upon which the life target is based.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention may take physical form in certain parts and arrangement ofparts, the preferred embodiment of which will be described in detail andillustrated in the accompanying drawings which form a part hereof, andwherein:

FIG. 1 is a schematic diagram of an exemplary architecture for a controlsystem and powertrain, in accordance with the present invention; and,

FIGS. 2 and 3 are algorithmic block diagrams, in accordance with thepresent invention;

FIG. 4 is a logic flowchart, in accordance with the present invention;and,

FIGS. 5 and 6 comprise analytical datagraphs, in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring now to the drawings, wherein the showings are for the purposeof illustrating the invention only and not for the purpose of limitingthe same, FIG. 1 shows a control system and an exemplary hybridpowertrain system which has been constructed in accordance with anembodiment of the invention. The exemplary hybrid powertrain systemcomprises a plurality of torque-generative devices operable to supplymotive torque to a transmission device, which supplies motive torque toa driveline. The torque-generative devices preferably comprise aninternal combustion engine 14 and first and second electric machines 56,72 operable to convert electrical energy supplied from an electricalstorage device 74 to motive torque. The exemplary transmission device 10comprises a two-mode, compound-split electro-mechanical transmissionhaving four fixed gear ratios, and includes a plurality of gearsoperable to transmit the motive torque to an output shaft 64 anddriveline through a plurality of torque-transfer devices containedtherein. Mechanical aspects of exemplary transmission 10 are disclosedin detail in U.S. Pat. No. 6,953,409, entitled “Two-Mode,Compound-Split, Hybrid Electro-Mechanical Transmission having Four FixedRatios”, which is incorporated herein by reference.

The control system comprises a distributed control module architectureinteracting via a local area communications network to provide ongoingcontrol to the powertrain system, including the engine 14, theelectrical machines 56, 72, and the transmission 10.

The exemplary powertrain system been constructed in accordance with anembodiment of the present invention. The hybrid transmission 10 receivesinput torque from torque-generative devices, including the engine 14 andthe electrical machines 56, 72, as a result of energy conversion fromfuel or electrical potential stored in electrical energy storage device(ESD) 74. The ESD 74 typically comprises one or more batteries. Otherelectrical energy storage devices that have the ability to storeelectric power and dispense electric power may be used in place of thebatteries without altering the concepts of the present invention. TheESD 74 is preferably sized based upon factors including regenerativerequirements, application issues related to typical road grade andtemperature, and, propulsion requirements such as emissions, powerassist and electric range. The ESD 74 is high voltage DC-coupled totransmission power inverter module (TPIM) 19 via DC lines referred to astransfer conductor 27. The TPIM 19 transfers electrical energy to thefirst electrical machine 56 by transfer conductors 29, and the TPIM 19similarly transfer electrical energy to the second electrical machine 72by transfer conductors 3 1. Electrical current is transferable betweenthe electrical machines 56, 72 and the ESD 74 in accordance with whetherthe ESD 74 is being charged or discharged. TPIM 19 includes the pair ofpower inverters and respective motor control modules configured toreceive motor control commands and control inverter states therefrom forproviding motor drive or regeneration functionality.

The electrical machines 56, 72 preferably comprise knownmotors/generator devices. In motoring control, the respective inverterreceives current from the ESD and provides AC current to the respectivemotor over transfer conductors 29 and 31. In regeneration control, therespective inverter receives AC current from the motor over therespective transfer conductor and provides current to the DC lines 27.The net DC current provided to or from the inverters determines thecharge or discharge operating mode of the electrical energy storagedevice 74. Preferably, machine A 56 and machine B 72 are three-phase ACelectrical machines and the inverters comprise complementary three-phasepower electronic devices.

The elements shown in FIG. 1, and described hereinafter, comprise asubset of an overall vehicle control architecture, and are operable toprovide coordinated system control of the powertrain system describedherein. The control system is operable to gather and synthesizepertinent information and inputs, and execute algorithms to controlvarious actuators to achieve control targets, including such parametersas fuel economy, emissions, performance, driveability, and protection ofhardware, including batteries of ESD 74 and motors 56, 72. Thedistributed control module architecture of the control system comprisesan engine control module (‘ECM’) 23, transmission control module (‘TCM’)17, battery pack control module (‘BPCM’) 21, and the Transmission PowerInverter Module (‘TPIM’) 19. A hybrid control module (‘HCP’) 5 providesoverarching control and coordination of the aforementioned controlmodules. There is a User Interface (‘UI’) 13 operably connected to aplurality of devices through which a vehicle operator typically controlsor directs operation of the powertrain, including the transmission 10.Exemplary vehicle operator inputs to the UI 13 include an acceleratorpedal, a brake pedal, transmission gear selector, and, vehicle speedcruise control. Within the control system, each of the aforementionedcontrol modules communicates with other control modules, sensors, andactuators via a local area network (‘LAN’) communications bus 6. The LANbus 6 allows for structured communication of control parameters andcommands between the various control modules. The specific communicationprotocol utilized is application-specific. By way of example, onecommunications protocol is the Society of Automotive Engineers standardJ1939. The LAN bus and appropriate protocols provide for robustmessaging and multi-control module interfacing between theaforementioned control modules, and other control modules providingfunctionality such as antilock brakes, traction control, and vehiclestability.

The HCP 5 provides overarching control of the hybrid powertrain system,serving to coordinate operation of the ECM 23, TCM 17, TPIM 19, and BPCM21. Based upon various input signals from the UI 13 and the powertrain,the HCP 5 generates various commands, including: an engine torquecommand; clutch torque commands for various clutches of the hybridtransmission 10; and motor torque commands for the electrical machines Aand B, respectively.

The ECM 23 is operably connected to the engine 14, and functions toacquire data from a variety of sensors and control a variety ofactuators, respectively, of the engine 14 over a plurality of discretelines collectively shown as aggregate line 35. The ECM 23 receives theengine torque command from the HCP 5, and generates an axle torquerequest. For simplicity, ECM 23 is shown generally having bi-directionalinterface with engine 14 via aggregate line 35. Various parameters thatare sensed by ECM 23 include engine coolant temperature, engine inputspeed to the transmission, manifold pressure, ambient air temperature,and ambient pressure. Various actuators that may be controlled by theECM 23 include fuel injectors, ignition modules, and throttle controlmodules.

The TCM 17 is operably connected to the transmission 10 and functions toacquire data from a variety of sensors and provide command controlsignals, i.e. clutch torque commands to the clutches of thetransmission.

The BPCM 21 interacts with various sensors associated with the ESD 74 toderive information about the state of the ESD 74 to the HCP 5. Suchsensors comprise voltage and electrical current sensors, as well asambient sensors operable to measure operating conditions of the ESD 74including, e.g., temperature and internal resistance of the ESD 74.Sensed parameters include ESD voltage, V_(BAT), ESD current, I_(BAT),and ESD temperature, T_(BAT). Derived parameters preferably include, ESDinternal resistance, R_(BAT), ESD state-of-charge, SOC, and other statesof the ESD, including available electrical power, P_(BAT) _(—) _(MIN)and P_(BAT) _(—) _(MAX).

The Transmission Power Inverter Module (TPIM) 19 includes theaforementioned power inverters and machine control modules configured toreceive motor control commands and control inverter states therefrom toprovide motor drive or regeneration functionality. The TPIM 19 isoperable to generate torque commands for machines A and B based uponinput from the HCP 5, which is driven by operator input through UI 13and system operating parameters. Motor torques are implemented by thecontrol system, including the TPIM 19, to control the machines A and B.Individual motor speed signals are derived by the TPIM 19 from the motorphase information or conventional rotation sensors. The TPIM 19determines and communicates motor speeds to the HCP 5.

Each of the aforementioned control modules of the control system ispreferably a general-purpose digital computer generally comprising amicroprocessor or central processing unit, read only memory (ROM),random access memory (RAM), electrically programmable read only memory(EPROM), high speed clock, analog to digital (A/D) and digital to analog(D/A) circuitry, and input/output circuitry and devices (I/O) andappropriate signal conditioning and buffer circuitry. Each controlmodule has a set of control algorithms, comprising resident programinstructions and calibrations stored in ROM and executed to provide therespective functions of each computer. Information transfer between thevarious computers is preferably accomplished using the aforementionedLAN 6.

Algorithms for control and state estimation in each of the controlmodules are typically executed during preset loop cycles such that eachalgorithm is executed at least once each loop cycle. Algorithms storedin the non-volatile memory devices are executed by one of the centralprocessing units and are operable to monitor inputs from the sensingdevices and execute control and diagnostic routines to control operationof the respective device, using preset calibrations. Loop cycles aretypically executed at regular intervals, for example each 3.125, 6.25,12.5, 25 and 100 milliseconds during ongoing engine and vehicleoperation. Alternatively, algorithms may be executed in response tooccurrence of an event.

The action described hereinafter occurs during active operation of thevehicle, i.e. that period of time when operation of the engine andelectrical machines are enabled by the vehicle operator, typicallythrough a ‘key-on’ action. Quiescent periods include periods of timewhen operation of the engine and electrical machines are disabled by thevehicle operator, typically through a ‘key-off’ action. In response toan operator's action, as captured by the UI 13, the supervisory HCPcontrol module 5 and one or more of the other control modules determinerequired transmission output torque, T_(O). Selectively operatedcomponents of the hybrid transmission 10 are appropriately controlledand manipulated to respond to the operator demand. For example, in theexemplary embodiment shown in FIG. 1, when the operator has selected aforward drive range and manipulates either the accelerator pedal or thebrake pedal, the HCP 5 determines how and when the vehicle is toaccelerate or decelerate. The HCP 5 also monitors the parametric statesof the torque-generative devices, and determines the output of thetransmission required to effect a desired rate of acceleration ordeceleration. Under the direction of the HCP 5, the transmission 10operates over a range of output speeds from slow to fast in order tomeet the operator demand.

Referring now to FIG. 2, a method and apparatus to estimate astate-of-life (‘SOL’) of an energy storage device useable in a hybridcontrol system in real-time is described. The exemplary method andapparatus to estimate state-of-life (‘SOL’) of the energy storage devicein the hybrid control system in real-time is disclosed in detail in U.S.patent application Ser. No. __/______, Attorney Docket No. GP-308433,entitled “Method and Apparatus for Real-Time Life Estimation of anElectric Energy Storage Device in a Hybrid Electric Vehicle”, which isincorporated herein by reference. The exemplary method and apparatus toestimate state-of-life comprises an algorithm that monitors anelectrical current and a state-of-charge and temperature of theelectrical energy storage device 74 during operation. Temperature of theelectrical energy storage device 74 is further monitored duringquiescent periods of ESD operation. Quiescent periods of ESD operationare characterized by ESD power flow that is de minimus whereas activeperiods of ESD operation are characterized by ESD power flow that is notde minimus. That is to say, quiescent periods of ESD operation aregenerally characterized by no or minimal current flow into or out of theESD. With respect to an ESD associated with a hybrid vehicle propulsionsystem for example, quiescent periods of ESD operation may be associatedwith periods of vehicle inactivity (e.g. powertrain, including electricmachines, is inoperative such as during periods when the vehicle is notbeing driven and accessory loads are off but may include such periodscharacterized by parasitic current draws as are required for continuingcertain controller operations including, for example, the operationsassociated with the present invention). Active periods of ESD operationin contrast may be associated with periods of vehicle activity (e.g.accessory loads are on and/or the powertrain, including electricmachines, is operative such as during periods when the vehicle is beingdriven wherein current flows may be into or out of the ESD). Thestate-of-life (‘SOL’) of the electrical energy storage device 74 isdetermined based upon the ESD current, the state-of-charge of the ESD,and the temperature of the ESD during quiescent and active periods ofoperation. The inputs to calculation of SOL, include ESD internalresistance R_(BAT), ESD temperature T_(BAT), ESD state-of-charge SOC,and ESD current I_(BAT). These are known operating parameters measuredor derived within the distributed control system. From these parameters,an A-h integration factor 110, a depth of discharge (‘DOD’) factor 112,a driving temperature factor, T_(DRIVE), 114 and a resting temperaturefactor, T_(REST), 116 are determined, and provided as input to determinea parameter for SOL. The operating parameters used to calculate SOLinclude: ESD current, I_(BAT), which is monitored in real-time, measuredin amperes, and integrated as a function of time; magnitude ofelectrical current flowing through the ESD 74 during each activecharging and discharging event; ESD state-of-charge (‘SOC’), includingdepth-of-discharge (‘DOD’); ESD temperature factor during active periodsof operation, T_(DRIVE), and ESD temperature factor during inactiveperiods of operation, T_(REST).

Referring again to FIG. 2, a schematic diagram is shown, demonstratingan exemplary method for estimating the state-of-life of the ESD 74 inreal-time, based upon monitored inputs. The method is preferablyexecuted as one or more algorithms in one of the controllers of thecontrol system, typically the HCP 5. The estimated state-of-life of theESD 74 (‘SOL_(K)’) is preferably stored as a scalar value in anon-volatile memory location for reference, updating, and for resetting,each occurring at appropriate points during life of the vehicle and theESD 74. Overall, determining a parametric value for the SOL comprisesmonitoring in real-time an ESD current I_(BAT) (in amperes), an ESDtemperature T_(BAT), an ESD voltage V_(BAT), an ESD resistance R_(BAT),and a ESD state-of-charge (‘SOC’). Each of the aforementioned factors,i.e. the integrated ESD current, depth of discharge, driving temperaturefactor, and resting temperature factor, are combined, preferably by asumming operation, with a previously determined state-of-life factor,SOL_(K), to determine a parametric value for the SOL, i.e. SOL_(K+1),shown as an output to block 120. The algorithm to determine thestate-of-life factor, SOL_(K+1), is preferably executed multiple timesduring each trip. When the engine/vehicle is initially started or turnedon, there is an initial state-of-life factor, SOL_(K), which is used incalculating subsequent values for SOL, and is shown as SOL_(SAVED) 128.The SOL_(SAVED) factor 128 is only used once during each trip, and issupplanted in future calculations during the trip the SOL_(K+1) factoroutput from Blocks 120, 122, and 124, which is shown as Block 130.Similarly, the resting temperature factor output from Block 116 is onlyused during the first execution of the algorithm to calculate SOL afterthe engine/vehicle is initially started or turned on, as is indicated bythe INIT block 126. On subsequent executions of the algorithm tocalculate SOL, the resting temperature factor is omitted from thecalculation of SOL.

Referring now to FIG. 3, a method and apparatus to predict or estimate aplurality of future or potential life gradients of a state-of-lifeparameter of an energy storage device useable in a hybrid control systemin real-time is described. The exemplary method and apparatus toestimate the plurality of future life gradients of the state-of-life(‘SOL’) of the energy storage device in the hybrid control system inreal-time is disclosed in detail in U.S. patent application Ser. No.__/______, Attorney Docket No. GP-308435, entitled “Method for Operatinga Hybrid Electric Powertrain Based on Predictive Effects Upon anElectric Energy Storage Device”. Therein is described a method andapparatus for calculating, a priori, a range of effects on state-of-lifeof an electrical energy storage device for a hybrid vehicle. The methodincludes determining potential changes in an operating state for theelectrical energy storage device. This includes selecting an array ofpotential values for an operating parameter e.g. electrical current,over a continuum from a maximum charging current to a maximumdischarging current, from which is determined or predicted acorresponding array of effects or changes upon operating state values,e.g. effects upon state-of-life. Each predicted change in the operatingstate is determined based upon and corresponding to one of the array ofvalues for the operating parameter of the electrical energy storagedevice. The predicted change in the state-of-life is based upon:time-based integration of the electrical current, depth of discharge ofthe energy storage device, and, operating temperature of the electricalenergy storage device, which are determined for each of the array ofpotential values for electrical current.

Referring now to FIG. 4, a control algorithm for hybrid vehicleoperation which targets a life objective for the electrical energystorage device 74 is now described. The algorithm is preferably executedin the aforementioned control system of the hybrid vehicle, preferablyduring one of the loop cycles, to effect real-time control andadjustments to the operation of the powertrain based upon prior use ofthe hybrid vehicle and the ESD 74. A primary control objective of thealgorithm comprises controlling operation of the electrical machines 56,72, including motive torque outputs, in charging and discharging, tomanage life of the ESD 74.

In the exemplary system, ESD power, P_(BAT), as a parameter that affectsservice life of the energy storage system 74, and is controllable by thehybrid control system. ESD power, P_(BAT)=I_(BAT)̂2/R_(BAT). Arelationship between the parametric value for ESD power, P_(BAT) and atarget life objective for the ESD is established. This permitsgeneration of a control algorithm which is operative to ongoingly andregularly control electrical power exchanged between ESD 74 to theelectrical motors 56, 72 such that the operating state, e.g.state-of-life (SOL), of the ESD is less than a predetermined value whenthe target life objective for the ESD is attained. The control algorithmis preferably executed by the control system during one of thepreviously described preset loop cycles. This algorithm is described indetail hereinbelow.

Referring again to FIG. 4, in overall operation, the algorithm uses asinput parameters a normalized value for state-of-life (SOL) of the ESD,a time-based state-of-life gradient based upon ESD power, an accumulatedelapsed time in service, and an accumulated distance. A normalized lifefactor is calculated based upon the accumulated time, and accumulateddistance (Block 200). The normalized life factor, output from block 200,and the normalized value for state-of-life are used to calculate arequired, desired or target gradient for life (Block 210). Thetime-based state-of-life gradient based upon ESD power is normalizedalong the time axis (Block 220). The required gradient for life, outputfrom block 210 and the normalized state-of-life gradient based upon ESDpower output from block 220, both converted to a z-domain, comprising anormalized domain ranging from 0.0 to 1.0, are input to a cost function(block 230) which generates an output of cost associated with ESD power,P_(BAT).

The preferred operating state, i.e. the state-of-life (SOL) parameterdescribed hereinabove, is normalized as follows:

SOL=0, for a new unused ESD, e.g. at start of service life; and,

SOL=1, for a fully expended ESD, e.g. at an end of service life (‘EOL’).

The normalized life factor output (in the z-domain) from Block 200 isdetermined as follows. The energy storage system has a target lifeobjective defined in terms of time and/or distance. For example, ahybrid vehicle might specify a target life objective in terms of time of8 years and a target life objective in terms of distance of 160,000kilometers (100,000 miles). In this example, an exemplary ESD whichremains in service for eight years or 160,000 kilometers (100,000 miles)of operation has met the target life objective.

The accumulated time, also referred to as a Total ESD Time, is definedas the total cumulative time that the energy storage system has been inservice, including all periods of vehicle activity and inactivity andall active and quiescent periods of ESD operation. In this embodiment,the ECM preferably includes a timing device which is able to measure andrecord elapsed operation time, including time when the vehicle ignitionis off and the system powered down. Under a circumstance wherein aparticular ESD is replaced with a new ESD, the accumulated time value isreset to zero. Under a circumstance wherein a particular ESD is replacedwith a partially expended or used ESD, the accumulated time is reset toan estimated total cumulative time that the partially expended ESD hadpreviously been in service. A normalized time life parameter is defined,using the same time units, as:

${{Normalized}\mspace{14mu} {Time}\mspace{14mu} {Life}\mspace{14mu} {Parameter}} = \frac{{Total}\mspace{14mu} {ESD}\mspace{14mu} {Time}}{{ESD}\mspace{14mu} {Time}\mspace{14mu} {Life}\mspace{14mu} {Target}}$

The ESD target life objective for time is 8 years for the exemplarysystem being described.

The accumulated distance, also referred to as a Total ESD Distance, isdefined as a total cumulative distance of operation with the ESD, whichis measurable in the ECM or other controller of the distributed controlarchitecture. Under a circumstance wherein a particular ESD is replacedwith a new system, the accumulated distance is reset to zero. Under acircumstance wherein a particular ESD is replaced with a partiallyexpended or used ESD, the accumulated distance can be reset to anestimated total cumulative distance that the expended or used ESDpreviously experienced. A normalized distance life parameter is defined,using the same distance units, as the following:

${{Normalized}\mspace{14mu} {Distance}\mspace{14mu} {Life}\mspace{14mu} {Parameter}} = \frac{{Total}\mspace{14mu} {ESD}\mspace{14mu} {Distance}}{{ESD}\mspace{14mu} {Distance}\mspace{14mu} {Life}\mspace{14mu} {Target}}$

The ESD target life objective for distance is 160,000 kilometers(100,000 miles) for the exemplary system being described.

Determining the Normalized Life Factor (in z-domain), output from block200, comprises capturing parametric values for accumulated time, i.e.Total ESD Time, and accumulated distance, i.e. Total ESD Distance, andnormalizing them as described herein above and wherein z=0 at the Startof Life Cycle of the ESD, i.e. when the timer for accumulated time andthe distance monitor for accumulated distance each begin counting; and,z=1 at the ESD target life objective, or Targeted End of Life (‘EOL’).

A preferred method for calculating the Normalized Life Parametercomprises selecting a maximum value between the Normalized Time LifeParameter and the Normalized Distance Life Parameter, shown below:

Normalized Life Parameter=MAXIMUM (Normalized Time Life Parameter,Normalized Distance Life Parameter)

In the exemplary embodiment, wherein ESD Time Life Target is 8 years andthe ESD Distance Life Target is 160,000 kilometers (100,000 miles), alinear budget of substantially 20,000 kilometers (12,500 miles) per yearof service is assumed. The Normalized Life Parameter could simply bedefined as follows, in Table 1:

TABLE 1 Dominating Factor Total ESD Total ESD (Time or Normalized LifeTime Distance Distance) Parameter (z) 4 years 32,000 km Time 0.50(20,000 miles) 2 years 80,000 km Distance 0.50 (50,000 miles) 4 years80,000 km Both 0.50 (50,000 miles) 9 years 112,000 km Time 1.00 = Target(70,000 miles) EOL 5 years 160,000 km Distance 1.00 = Target (100,000miles) EOL

Although the preferred embodiment of this invention involves the use oftime and/or distance in defining the definition of targeted end of life(‘EOL’), other parameters can be used.

The time domain parameters are converted to normalized life parameters,in the z-domain. It is desirable to be able to convert a differentialamount of run time (in dt) to a differential amount of Normalized LifeParameter (in dz), for ease of comparisons.

The percent of time the vehicle is operated, i.e. Total Vehicle RunTime, is compared to total in-service time of the vehicle, i.e. TotalVehicle Time, to estimate a percent of vehicle run time versus totalvehicle time. Total vehicle time ideally has the same value as Total ESDTime. The Total Vehicle Run Time Percentage is defined as follows:

${{Total}\mspace{14mu} {Vehicle}\mspace{14mu} {Run}\mspace{14mu} {Time}\mspace{14mu} {Percentage}} = \frac{{Total}\mspace{14mu} {Vehicle}\mspace{14mu} {Run}\mspace{14mu} {Time}}{{Total}\mspace{14mu} {Vehicle}\mspace{14mu} {Time}}$

In the exemplary embodiment, a vehicle that is determined to beoperating or running for 5% of total time (Total Vehicle Run TimePercentage=5%), the following analysis is shown with reference to Table2, below:

TABLE 2 Normalized Total Total Total Life ESD Total ESD ESD ESDDominating Parameter Time to Run Time Time Distance Factor (z) EOL toEOL 4 years 20,000 Time 0.50 4 years / 8 × 0.05 = miles 0.5 = 8 0.40years years 2 years 50,000 Distance 0.50 2 years / 4 × 0.05 miles 0.5 =4 0.20 years years

Referring again to Table 2, examples are provided to explain systemoperation. Exemplary values for two vehicles are shown, wherein TotalESD Time and Total ESD Distance are known. One of ESD Time and Distanceis determined to be a dominating factor based upon whether the exemplaryvehicle is likely to attain a target life objective of time or distance,as determinable based upon the Normalized Life Parameter. When thedominating factor is time, then the Total ESD Time to EOL equals theTarget Total ESD Time. When the dominating factor is Distance, thenTotal ESD Time to EOL equals is determined based upon Distance, and isless than the ESD Target time life objective.

When a new ESD is installed, thus setting z=0, Total ESD Run Time to EOLis the following:

Total ESD Run Time to EOL=Total Vehicle Run Time %×ESD Time Life Target

After the ESD has been used (z>0), the Total ESD Run Time to End of life(‘EOL’) is

${{Total}\mspace{14mu} {ESD}\mspace{14mu} {Run}\mspace{14mu} {Time}\mspace{14mu} {to}\mspace{14mu} {EOL}} = {{Total}\mspace{14mu} {Vehicle}\mspace{14mu} {Run}\mspace{14mu} {Time}\mspace{14mu} \% \times {\quad( \frac{{Total}\mspace{14mu} {ESD}\mspace{14mu} {Time}}{{Normalized}\mspace{14mu} {Life}\mspace{14mu} {Parameter}\mspace{14mu} (z)} )}}$

The Total ESD Run Time to EOL effectively converts differential changesin run time (dt) to differential changes in the Normalized LifeParameter (dz), i.e.,

${dz} = \frac{{dt}\mspace{14mu} ( \sec )}{{Total}\mspace{14mu} {ESD}\mspace{14mu} {Run}\mspace{14mu} {Time}\mspace{14mu} {EOL}\mspace{14mu} ( \sec )}$

The state-of-life gradient (dSOL/dt) estimated as a function ofelectrical current and ESD power (P_(BAT)), is described hereinabove,and comprises estimating ESD state-of-life time gradient as a functionof ESD Power for an array of preselected current levels.

Referring again to FIG. 4, it is relatively straightforward to normalizetime and transform a time gradient to a normalized gradient (notated asdSOL/dz). By example, when the targeted ESD life objective is defined asa run time, in seconds of Total ESD Run Time to EOL, the normalizedstate-of-life gradient is defined as follows:

$\frac{{SOL}}{z} = {{\frac{{SOL}}{t}\lbrack \frac{1}{\sec} \rbrack} \times {Total}\mspace{14mu} {ESD}\mspace{14mu} {Run}\mspace{14mu} {Time}\mspace{14mu} {to}\mspace{14mu} {{EOL}\mspace{14mu}\lbrack \sec \rbrack}}$

Note that normalized gradient is defined in such a way that if theenergy storage system averages a normalized gradient of one (1) or less,then the life objective is met. Similarly, if the normalized gradientaverages greater than one, then the life objective is not met.

This provides a way of coupling the target objective to a key controlvariable gradient. A control system must be designed to control ESDpower in such a way that at the end of the energy storage system lifetarget (z=1), the SOL is less than 1. That is, over the life of theenergy storage system (from z=0 to z=1), the average, and sincenormalized, the integral of dSOL/dz must be less than or equal to 1 forlife objectives to be met. More particularly, as shown in Eq. 1, whichis executable as an algorithm in the control system:

P_(BAT) such that

$\begin{matrix}{{{SOL}(1)} = {{\int_{0}^{1}{\frac{{SOL}}{z}( P_{BAT} )\ {z}}} \leq 1}} & \lbrack 1\rbrack\end{matrix}$

Referring now to FIG. 5, a datagraph showing performance of an exemplarysystem with an ESD operating using the system described herein, whereinthe x-axis comprises the normalized life factor of time or distance,converted to the z-domain, and the y-axis comprises the state-of-life(SOL). Line 90 comprises a representative system wherein a change in thestate-of-life of the ESD increases linearly with a change in thenormalized life factor in the z-domain, such that end of life criteriaare just met. Line 96 shows an actual system, having exemplary Points Aand B. Point A represents a system wherein ambient conditions oroperation of the system led to aggressive use of the ESD, and thus toadvanced aging of the ESD or high SOL of the ESD, such that it ispossible that the ESD may be expended before the target service life. Afirst line 92 comprises a normalized target gradient line for Point A,calculated from Point A to the end of life of the device which comprisesthe SOL meeting the normalized life factor. In the condition wherein thesystem has reached an operating condition shown as point A, the controlsystem estimates the array of parametric values for future SOL basedupon the array of ESD current levels, I_(BAT). The system is operable tomatch a parametric value for P_(BAT) and corresponding value for I_(BAT)that accomplishes the normalized gradient, using the algorithm developedin Eq. 1, above. This likely leads to less aggressive use of the ESDduring vehicle operation.

Point B represents a system wherein ambient conditions or operation ofthe system led to less aggressive use of the ESD, thus leading toretarded aging of the ESD or low SOL of the ESD, such that it ispossible that the ESD will not be expended upon reaching the targetservice life. A second line 94 comprises a normalized target gradientline for Point B, calculated from Point B to the end of life of thedevice which comprises the SOL meeting the normalized life factor. Inthe condition wherein the system has reached an operating conditionshown as point B, the control system estimates the array of parametricvalues for future SOL based upon the array of ESD current levels,I_(BAT). The system is operable to match a parametric value for P_(BAT)and corresponding value for I_(BAT) that accomplishes the normalizedgradient, using the algorithm developed in Eq. 1, above. This likelyleads to more aggressive use of the ESD during vehicle operation.

Referring now to FIGS. 6A, 6B, and 6C, further details of the operationof the system are provided. FIG. 6A shows a normalized SOL gradientplotted as a function of ESD power, P_(BAT), over a range that is acontinuum from charging to discharging the ESD, with exemplary targetgradient Points A and B, from FIG. 5. FIG. 6C shows a line demonstratingan operating cost as a function of the normalized SOL gradient, whereinthe target line, at the target gradient value, corresponds to the Line90 shown in FIG. 5. Operating costs generally comprise costs associatedwith fuel and electrical energy consumption associated with a specificoperating point of the powertrain system for the vehicle. This graphdemonstrates that there is a low operating cost associated with anormalized SOL gradient that is less than the target, i.e. falling belowLine 90 of FIG. 5. Conversely, operating cost increases as thenormalized SOL gradient increases greater than the target line. FIG. 6Bcan be constructed using information from FIGS. 6A and 6C, whereinoperating cost is plotted as a function of ESD power, P_(BAT), withlines representing costs associated with operating the exemplary systemstarting at Points A and B plotted, and correlated to analogousoperating points shown in FIG. 6A. It is readily demonstrated therelative magnitude of a cost differential associated with the same ESDpower, P_(BAT), at different initial starting points. In other words,operating with SOL above the target gradient, i.e. Line 90 of FIG. 5 isgenerally more costly and less preferred than operating with SOL at orbelow the target gradient. Thus, the control system can execute analgorithm operative to control the power transmitted from the electricalenergy storage device such that the electrical energy storage devicegenerally tracks and converges on the target gradient, preferably avoidsSOL in excess of the target gradient, and does not reach end-of-lifewhen the target life objective, e.g. time or distance, is attained.

The invention has been described with specific reference to thepreferred embodiments and modifications thereto. Further modificationsand alterations may occur to others upon reading and understanding thespecification. It is intended to include all such modifications andalterations insofar as they come within the scope of the invention.

1. Method for operating a hybrid electric powertrain including anelectrical energy storage device adapted for exchanging electricalenergy with a hybrid vehicular powertrain including first and secondelectric machines, each machine operable to impart torque to a two-mode,compound-split electro-mechanical transmission having four fixed gearratios and two continuously variable operating modes, comprising:providing present state-of-life of the electrical energy storage device;establishing a life target for the electrical energy storage device as apredetermined limit in a predetermined metric at a predeterminedstate-of-life of the electrical energy storage device; determining astate-of-life gradient with respect to the predetermined metric whichconverges the state-of-life of the electrical energy storage device tothe life target; and operating the electric machines such thatelectrical energy storage device state-of-life substantially tracks thestate-of-life gradient based on the determined changes in state-of-life.2. The method of claim 1 wherein the predetermined state-of-life of theelectrical energy storage device is indicative of the end of life of theelectrical energy storage device.
 3. The method as in claim 1 whereinthe predetermined metric comprises elapsed service time of theelectrical energy storage device.
 4. The method of claim 1 wherein thepredetermined metric comprises vehicle distance traveled.
 5. The methodof claim 1 wherein the life target is based upon a predetermined limitin one of elapsed service time of the electrical energy storage deviceand vehicle distance traveled.
 6. The method of claim 5 wherein the lifetarget is normalized with respect to the one of elapsed service time ofthe electrical energy storage device and vehicle distance traveled uponwhich the life target is based.
 7. Method for operating a hybridelectric powertrain including an electrical energy storage deviceadapted for exchanging electrical energy with a hybrid vehicularpowertrain including first and second electric machines, each machineoperable to impart torque to a two-mode, compound-splitelectro-mechanical transmission having four fixed gear ratios and twocontinuously variable operating modes, comprising: providing astate-of-life gradient based on a present state-of-life of theelectrical energy storage device and at least one predetermined limit ina predetermined metric; and controlling electrical energy storage devicecurrent during periods of vehicle activity such that electrical energystorage device state-of-life substantially tracks the state-of-lifegradient.
 8. The method of claim 7 wherein controlling electrical energystorage device current such that electrical energy storage devicestate-of-life substantially tracks the state-of-life gradient comprises:providing a plurality of predicted effects upon electrical energystorage device state-of-life based on a plurality of potentialelectrical energy storage device currents during periods of vehicleactivity; and controlling electrical energy storage device currentduring periods of vehicle activity based on the predicted effects andthe state-of-life gradient.
 9. The method of claim 8 wherein controllingelectrical energy storage device current during periods of vehicleactivity comprises: operating the electric machines based on thepredicted effects and the state-of-life gradient.
 10. Method foroperating a hybrid electric powertrain including an electrical energystorage device adapted for exchanging electrical energy with a hybridvehicular powertrain including first and second electric machines, eachmachine operable to impart torque to a two-mode, compound-splitelectro-mechanical transmission having four fixed gear ratios and twocontinuously variable operating modes, comprising: controlling powertransmitted between the electrical energy storage device and theelectric machines during periods of vehicle activity such that theoperating state of the electrical energy storage device is less than apredetermined value when a target life objective is attained.
 11. Themethod of claim 10, wherein the operating state of the electrical energystorage device comprises a state-of-life of the electrical energystorage device.
 12. The method of claim 11, wherein controlling powertransmitted from the electrical energy storage device during periods ofvehicle activity such that the state-of-life is less than apredetermined value when the target life objective is attained furthercomprises: calculating a life factor based upon an accumulated time andan accumulated distance of operation of the powertrain; determining atarget state-of-life gradient based upon the life factor, thestate-of-life, and the target life objective; and, controllingelectrical power between the electrical energy storage device and thepowertrain based upon the target state-of-life gradient.
 13. The methodof claim 12, wherein controlling electrical power between the electricalenergy storage device and the powertrain based upon the targetstate-of-life gradient further comprises: determining potential changesin state-of-life for the electrical energy storage device based upon anarray of potential electrical currents through the electrical energystorage device during periods of vehicle activity; and, selecting one ofthe array of potential electrical currents based upon the state-of-lifegradient.
 14. The method of claim 13, wherein determining potentialchanges in state-of-life for the electrical energy storage device basedupon an array of potential electrical currents through the electricalenergy storage device during periods of vehicle activity furthercomprises: selecting the array of potential electrical currents throughthe electrical energy storage device; and, determining a correspondingarray of changes in the state-of-life for the electrical energy storagedevice determined based upon the array of potential electrical currentsthrough the electrical energy storage device; wherein changes in thestate-of-life for the electrical energy storage device are determinedbased upon: time-based integration of the electrical currents throughthe electrical energy storage device, depth of discharge of the energystorage device, and, operating temperature of the electrical energystorage device.
 15. The method of claim 10, wherein controlling powertransmitted between the electrical energy storage device and theelectric machines during periods of vehicle activity such that theoperating state of the electrical energy storage device is less than apredetermined value further comprises: determining the operating stateof the electrical energy storage device, comprising: monitoringelectrical current through the electrical energy storage device;monitoring a state-of-charge of the electrical energy storage device;monitoring a temperature of the electrical energy storage device duringperiods of vehicle activity and inactivity; and, determining astate-of-life of the electrical energy storage device, based upon theelectrical energy storage device current, the state-of-charge of theelectrical energy storage device, and, the temperature of the electricalenergy storage device during periods of vehicle activity and inactivity.